期刊
BMJ GLOBAL HEALTH
卷 4, 期 4, 页码 -出版社
BMJ PUBLISHING GROUP
DOI: 10.1136/bmjgh-2019-001552
关键词
physical accessibility to health services; health services research; health service provision; health equity; health inequality; shortest travel time; sub-Saharan Africa
资金
- Wellcome Trust [206471/Z/17/Z]
- Wellcome Trust [206471/Z/17/Z] Funding Source: Wellcome Trust
Background Having hospitals located in urban areas where people, resources and wealth concentrate is efficient, but leaves long travel times for the rural and often poorer population and goes against the equity objective. We aimed to assess the current efficiency (mean travel time in the whole population) and equity (difference in travel time between the poorest and least poor deciles) of hospital care provision in four sub-Saharan African countries, and to compare them against their theoretical optima. Methods We overlaid the locations of 480, 115, 3787 and 256 hospitals in Kenya, Malawi, Nigeria and Tanzania, respectively, with high-resolution maps of travel time, population and wealth to estimate current efficiency and equity. To identify the potential optima, we simulated 7500 sets of hospitals locations based on various population and wealth weightings and percentage reallocations for each country. Results The average travel time ranged from 38 to 79min across countries, and the respective optima were mildly shorter (<15%). The observed equity gaps were wider than their optima. Compared with the best case scenarios, differences in the equity gaps varied from 7% in Tanzania to 77% in Nigeria. In Kenya, Malawi and Tanzania, narrower equity gaps without increasing average travel time were seen from simulations that held 75%-90% of hospitals at their current locations. Interpretations Current hospital distribution in the four sub-Saharan African countries could be considered efficient. Simultaneous gains in efficiency and equity do not necessarily require a fundamental redesign of the healthcare system. Our analytical approach is readily extendible to aid decision support in adding and upgrading existing hospitals.
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